Currently, new technologies such as wearable computing, mobile computing, and pervasive computing develop rapidly, which put forward new challenges and higher requirements for the human computer interaction technology and provide many new opportunities. In this phase, the nature and harmony human computer interaction manner gets a certain development, and the main characteristic thereof is an multi-channel interaction based on input means such as postures, voice, handwriting, tracking, and expressions, and the objective thereof is to make people perform an interaction operation in a nature way such as using an action, voice, and an expression, which is exactly “user freedom” emphasized by ideal human computer interaction.
In the traditional method for identifying a head movement, a myoelectricity sensor is disposed on the neck of a user, and when the user wants to turn the head, the neck muscles thereof drive the head of the user perform the head turning movement, and at this time, a corresponding myoelectricity signal may be detected, and based on the myoelectricity signal, the head movement of the user may be identified.
By using the foregoing method for identifying a head movement, a maximum amplitude of the detected myoelectricity signal is about 0.5 mV, which results in relatively poor identification accuracy.